Epigenomics and the kidney

Wilson, Parker C.; Ledru, Nicolas; Humphreys, Benjamin D.

doi:10.1097/mnh.0000000000000602

Cited by 12 publications

(10 citation statements)

References 33 publications

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“…Multiple scRNAseq atlases of mature human [10][11][12][13] and mouse kidney 14,15 have established how transcription contributes to cell-type specificity. Recent methods have expanded this approach to single-cell profiling of chromatin accessibility [16][17][18] . Single nucleus assay for transposase-accessible chromatin using sequencing (snATACseq) is an extension of bulk ATAC-seq 19 that employs hyperactive Tn5 transposase to measure chromatin accessibility in thousands of individual cells 17 .…”

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confidence: 99%

“…Single nucleus assay for transposase-accessible chromatin using sequencing (snATACseq) is an extension of bulk ATAC-seq 19 that employs hyperactive Tn5 transposase to measure chromatin accessibility in thousands of individual cells 17 . Chromatin accessibility is a dynamic process that drives nephron development and nephron progenitors have distinct chromatin accessibility profiles that change as they differentiate 18 . The role of chromatin accessibility in the promotion or inhibition of kidney repair and regeneration has important implications for designing therapies for acute and chronic kidney disease and may help to improve directed differentiation of kidney organoids 20 .…”

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Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

et al. 2021

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The integration of single cell transcriptome and chromatin accessibility datasets enables a deeper understanding of cell heterogeneity. We performed single nucleus ATAC (snATAC-seq) and RNA (snRNA-seq) sequencing to generate paired, cell-type-specific chromatin accessibility and transcriptional profiles of the adult human kidney. We demonstrate that snATAC-seq is comparable to snRNA-seq in the assignment of cell identity and can further refine our understanding of functional heterogeneity in the nephron. The majority of differentially accessible chromatin regions are localized to promoters and a significant proportion are closely associated with differentially expressed genes. Cell-type-specific enrichment of transcription factor binding motifs implicates the activation of NF-κB that promotes VCAM1 expression and drives transition between a subpopulation of proximal tubule epithelial cells. Our multi-omics approach improves the ability to detect unique cell states within the kidney and redefines cellular heterogeneity in the proximal tubule and thick ascending limb.

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Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

et al. 2021

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“…Intriguingly also in adults about 10% of kidney diseases are due to a genetic cause (Groopman et al 2019 ). Thus, these new technologies may lead to new insights in adult nephrology allowing a reclassification of diagnosis and treatment (Leveson and Oates 2020 ; Wilson et al 2020 ).…”

Section: Which Datasets Can Be Used In Systems Nephrologymentioning

confidence: 99%

“…The advances in high-throughput sequencing technologies in recent years also facilitate a precise analysis of the epigenetic landscape. Approaches include among others the measurement of transcription factor (TF) binding and histone modifications by chromatin immunoprecipitation sequencing (ChIP-seq), and the detection of DNA methylation by bisulfite sequencing, the analysis of chromatin accessibility using the Assay of Transposase Accessible Chromatin Sequencing (ATAC-seq) (Li et al 2019 ; Wilson et al 2020 ).…”

Section: Which Datasets Can Be Used In Systems Nephrologymentioning

confidence: 99%

Perspectives in systems nephrology

et al. 2021

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Chronic kidney diseases (CKD) are a major health problem affecting approximately 10% of the world’s population and posing increasing challenges to the healthcare system. While CKD encompasses a broad spectrum of pathological processes and diverse etiologies, the classification of kidney disease is currently based on clinical findings or histopathological categorizations. This descriptive classification is agnostic towards the underlying disease mechanisms and has limited progress towards the ability to predict disease prognosis and treatment responses. To gain better insight into the complex and heterogeneous disease pathophysiology of CKD, a systems biology approach can be transformative. Rather than examining one factor or pathway at a time, as in the reductionist approach, with this strategy a broad spectrum of information is integrated, including comprehensive multi-omics data, clinical phenotypic information, and clinicopathological parameters. In recent years, rapid advances in mathematical, statistical, computational, and artificial intelligence methods enable the mapping of diverse big data sets. This holistic approach aims to identify the molecular basis of CKD subtypes as well as individual determinants of disease manifestation in a given patient. The emerging mechanism-based patient stratification and disease classification will lead to improved prognostic and predictive diagnostics and the discovery of novel molecular disease-specific therapies.

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“…Important findings on kidney disease pathophysiology have already been accomplished by omics science, i.e., genomics [ 3 , 4 ], epigenomics [ 5 ], transcriptomics [ 6 ], and proteomics [ 7 ]. One of the latest additions to the omics research field is metabolomics, the quantitative study of small organic compounds, called metabolites, present in a biological specimen [ 8 ].…”

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Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

et al. 2021

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Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.

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Epigenomics and the kidney

Cited by 12 publications

References 33 publications

Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

Perspectives in systems nephrology

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

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